Package: BinaryEPPM
Type: Package
Title: Mean and Scale-Factor Modeling of Under- And Over-Dispersed
        Binary Data
Version: 3.0
Imports: Formula, expm, numDeriv, stats, lmtest, grDevices, graphics
Date: 2024-06-03
Authors@R: c(person(c("David", "M."), "Smith", role = c("aut", "cre"),
                    email = "dmccsmith@verizon.net"),
             person(c("Malcolm", "J."), "Faddy", role = "aut"))
Depends: R (>= 3.5.0)
Description: Under- and over-dispersed binary data are modeled using an
        extended Poisson process model (EPPM) appropriate for binary
        data. A feature of the model is that the under-dispersion
        relative to the binomial distribution only needs to be greater
        than zero, but the over-dispersion is restricted compared to
        other distributional models such as the beta and correlated
        binomials. Because of this, the examples focus on
        under-dispersed data and how, in combination with the beta or
        correlated distributions, flexible models can be fitted to data
        displaying both under- and over-dispersion. Using Generalized
        Linear Model (GLM) terminology, the functions utilize linear
        predictors for the probability of success and scale-factor with
        various link functions for p, and log link for scale-factor, to
        fit a variety of models relevant to areas such as bioassay.
        Details of the EPPM are in Faddy and Smith (2012)
        <doi:10.1002/bimj.201100214> and Smith and Faddy (2019)
        <doi:10.18637/jss.v090.i08>.
License: GPL-2
Suggests: R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2026-06-21 06:51:08 UTC; root
Author: David M. Smith [aut, cre], Malcolm J. Faddy [aut]
Maintainer: David M. Smith <dmccsmith@verizon.net>
Repository: https://cran.r-universe.dev
Date/Publication: 2024-06-05 02:41:28 UTC
RemoteUrl: https://github.com/cran/BinaryEPPM
RemoteRef: HEAD
RemoteSha: 3e932ad7447601b73b03cf81296dc61e34adc642